Associations of Nasopharyngeal Metabolome and Microbiome with Severity among Infants with Bronchiolitis. A Multiomic Analysis - Stewart, Christopher J. (Am J Respir Crit Care Med, 2017)
Rationale: Bronchiolitis is the most common lower respiratory infection in infants; however, it remains unclear which infants with bronchiolitis will develop severe illness. In addition, although emerging evidence indicates associations of the upper-airway microbiome with bronchiolitis severity, little is known about the mechanisms linking airway microbes and host response to disease severity. Objectives: To determine the relations among the nasopharyngeal airway metabolome profiles, microbiome profiles, and severity in infants with bronchiolitis. Methods: We conducted a multicenter prospective cohort study of infants (age <1 yr) hospitalized with bronchiolitis. By applying metabolomic and metagenomic (16S ribosomal RNA gene and whole-genome shotgun sequencing) approaches to 144 nasopharyngeal airway samples collected within 24 hours of hospitalization, we determined metabolome and microbiome profiles and their association with higher severity, defined by the use of positive pressure ventilation (i.e., continuous positive airway pressure and/or intubation). Measurements and Main Results: Nasopharyngeal airway metabolome profiles significantly differed by bronchiolitis severity (P < 0.001). Among 254 metabolites identified, a panel of 25 metabolites showed high sensitivity (84%) and specificity (86%) in predicting the use of positive pressure ventilation. The intensity of these metabolites was correlated with relative abundance of Streptococcus pneumoniae. In the pathway analysis, sphingolipid metabolism was the most significantly enriched subpathway in infants with positive pressure ventilation use compared with those without (P < 0.001). Enrichment of sphingolipid metabolites was positively correlated with the relative abundance of S. pneumoniae. Conclusions: Although further validation is needed, our multiomic analyses demonstrate the potential of metabolomics to predict bronchiolitis severity and better understand microbe–host interaction.